The development of saturation diving in civil and defense applications has enabled man to work in the sea at great depths and for long periods of time. This advance has resulted, in part, as a consequence of the substitution of helium for nitrogen in breathing gas mixtures. However, utilization of HeO2 breathing mixture at high ambient pressures has caused problems in speech communication; in turn, helium speech enhancement systems have been developed to improve diver communication. These speech unscramblers attempt to process variously the grossly unintelligible speech resulting from the effect of breathing mixtures and ambient pressure, and to reconstruct such signals in order to provide adequate voice communication. It is known that the glottal excitation is quasi-periodic and the vocal tract filter is quasi-stationary. Hence, it is possible to use an auto regressive modelisation to restore speech intelligibility in hyperbaric conditions. Corrections are made on the vocal tract transfer function, either in the frequency domain, or directly on the autocorrelation function. A spectral subtraction or noise reduction may be added to improve speech quality. A new VAD enhanced helium speech unscrambler is proposed for use in adverse conditions or in speech recognition. This system, implementable on single chip DSP of current technology, is capable to work in real time.

This paper presents the subjective speech quality evaluation in terms of the Mean Opinion Score (MOS) and the relationship between BER and subjective speech quality in a GSM-based radio system. The results show that in certain environments (hilly terrain and rural areas), a SNR (or C/I) higher than 12 dB is required for acceptable speech quality. For an acceptable speech quality, a BER(c1) better than 10-2 is needed in a GSM-based system.

This paper is concerned with the validation of simple turning points of two-point boundary value problems of nonlinear ordinary differential equations. Usually it is hard to validate approximate solutions of turning points numerically because of it's singularity. In this paper, it is pointed out that applying the infinite dimensional Krawcyzk-based interval validation method to enlarged system, the existence of simple turning points can be verified. Taking an example, the result of validation is also presented.

Modeling error is the major concerning issue in the trajectory estimation. This paper formulates the dynamic model of a reentry vehicle in reentry phase for identification with an unmodeled acceleration input covering possible model errors. Moreover, this work presents a novel on-line estimation approach, adaptive filter, to identify the trajectory of a reentry vehicle from a single radar measured data. This proposed approach combines the extended Kalman filter and the recursive least-squares estimator of input with the hypothetical testing scheme. The recursive least-squares estimator is provided not only to extract the magnitude of the unmodeled input but to offer a testing criterion to detect the onset and presence of the input. Numerical simulation demonstrates the superior capabilities in accuracy and robustness of the proposed method. In real flight analysis, the adaptive filter also performs an excellent estimation and prediction performances. The recommended trajectory estimation method can support defense and tactical operations for anti-tactical ballistic missile warfare.

The naturalness of normal sustained vowels is considered to be attributable to the fluctuations observed in the steady part where speech signal is seemingly almost periodic. There always exist two kinds of involuntary fluctuations in the steady part of sustained vowels, even if the sustained vowels are phonated as steadily as possible. One is pitch period fluctuation and the other is waveform fluctuation. In this study, frequency analyses on these fluctuations were conducted in order to investigate their general characteristics. The results of the analyses suggested that the frequency characteristics of the fluctuations were possible to be approximated as 1/fβ-like, which is regarded as the specific feature of random fractal. Therefore, a procedure based on random fractal generation methods was proposed in order to produce these fluctuations for the improvement of the voice quality of synthesized sustained vowels. A series of psychoacoustic experiments was also conducted to evaluate the proposed technique. Experimental results indicated that the proposed technique was effective for synthesized sustained vowels to be perceived as human-like. Unlike the sustained vowels which were synthesized without pitch period fluctuation nor waveform fluctuation, the synthesized sustained vowels which contained the fluctuations were not perceived as buzzer-like, which is the major problem of the voice quality of synthesized sustained vowels. However, it was also found that both of the fluctuations were not always the acoustic cues for the naturalness of normal sustained vowels. The synthesized sustained vowels which contained the fluctuations whose frequency characteristics were the same as that of white noise were perceived as noise-like, which is not at all the voice quality of normal sustained vowels. The results of psychoacoustic experiments indicated that the frequency characteristics of the fluctuations, which are possible to be modeled as 1/fβ-like, were the significant factors for the naturalness of normal sustained vowels.

We propose an information integration architecture for a man-machine interface to construct a new agent-based Computer Supported Cooperative Work (CSCW) system. The system acts as a clerk in cooperative work giving users the advantage of using cooperative work space. The system allows users to do their work in the style of an ordinary meeting because spontaneous expressions of speech and gestures by users are detected by sensors so that they can be integrated with a task model at several levels to create suitable responses in a man-machine interface. As a result, users can dedicate themselves to mutually understand other meeting members with no awareness of direction to the CSCW system. In this paper, we describe the whole system and its information integration architecture for the man-machine interface including, the principle of functions, the current status of the system and future directions.

This paper presents a method which can effectively acquire free space on a plane for moving forward in safety by using height information of objects. This method can be applied to free space extraction on a road, and, in short, it is a road extraction method for an autonomous vehicle. Since a road area can be assumed to be a sequence of flat planes in front of a vehicle, it is effective to apply the inverse perspective projection model to the ground plane. However, conventional methods using this model have a drawback in that some areas on the road plane are wrongly detected as obstacle areas since these methods are sensitive to the error of the camera geometry with respect to the assumed plane. In order to overcome this drawback, the proposed approach named the Planar Projection Stereopsis (PPS) method supplies, to the road extraction method using the inverse perspective projection model, a contrivance for removing these erroneous areas effectively. Since PPS uses the inverse perspective projection model, both left and right images are projected to the road plane and obstacle areas are detected by examining the difference between these projected images. Because detected obstacle areas include a lot of erroneous areas, PPS examines the shapes of the obstacle areas and eliminates falsely detected areas on the road plane by using the following properties: obstacles whose heights are different from the road plane are projected to the shapes falling backward from the location where the obstacles touch the road plane; and the length of shapes falling backward depends on the location of obstacles in relation to the stereoscopic cameras and the height of obstacles in relation to the road plane. Experimental results for real road scenes have shown the effectiveness of the proposed method. The quantitative evaluation of the results has shown that on average 89. 3% of the real road area can be extracted and the average of the falsely extracted ratio is 1. 4%. Since the road area can be extracted by simple projection of images and subtraction of projected images from a set of stereo images, our method can be applied to real-time operation.

Recently, a trellis-based recursive maximum likelihood decoding (RMLD) algorithm has been proposed for decoding binary linear block codes. This RMLD algorithm is computationally more efficient than the Viterbi decoding algorithm. However, the computational complexity of the RMLD algorithm depends on the sectionalization of a code trellis. In general, minimization of the computational complexity results in non-uniform sectionalization of a code trellis. From implementation point of view, uniform sectionalization of a code trellis and regularity among the trellis sections are desirable. In this paper, we apply the RMLD algorithm to a class of codes which are transitive invariant. This class includes Reed-Muller (RM) codes, the extended and permuted BCH (EBCH) codes and their subcodes. For this class of codes, the binary uniform sectionalization of a code trellis results in the following regular structure. At each step of decoding recursion, the metric table construction procedure is applied uniformly to all the sections and the size and structure of each metric table are the same. This simplifies the implementation of the RMLD algorithm. Furthermore, for all RM codes of lengths 64 and 128 and EBCH codes of lengths 64 and 128 with relatively low rate, the computational complexity of the RMLD algorithm based on the binary uniform sectionalization of a code trellis is almost the same as that based on an optimum sectionalization of a code trellis.

Conventional approaches to neural network training do not consider possibility of selecting training samples dynamically during the learning phase. Neural network is simply presented with the complete training set at each iteration of the learning. The learning can then become very costly for large data sets. Huge redundancy of data samples may lead to the ill-conditioned training problem. Ill-conditioning during the training causes rank-deficiencies of error and Jacobean matrices, which results in slower convergence speed, or in the worst case, the failure of the algorithm to progress. Rank-deficiencies of essential matrices can be avoided by an appropriate selection of training exemplars at each iteration of training. This article presents underlying theoretical grounds for dynamic sample selection (DSS), that is mechanism enabling to select a subset of training set at each iteration. Theoretical material is first presented for general objective functions, and then for the objective functions satisfying the Lipschitz continuity condition. Furthermore, implementation specifics of DSS to first order line search techniques are theoretically described.

Computational expensiveness of the training techniques, due to the extensiveness of the data set, is among the most important factors in machine learning and neural networks. Oversized data set may cause rank-deficiencies of Jacobean matrix which plays essential role in training techniques. Then the training becomes not only computationally expensive but also ineffective. In [1] the authors introduced the theoretical grounds for dynamic sample selection having a potential of eliminating rank-deficiencies. This study addresses the implementation issues of the dynamic sample selection based on the theoretical material presented in [1]. The authors propose a sample selection algorithm implementable into an arbitrary optimization technique. An ability of the algorithm to select a proper set of samples at each iteration of the training has been observed to be very beneficial as indicated by several experiments. Recently proposed approaches to sample selection work reasonably well if pattern-weight ratio is close to 1. Small improvements can be detected also at the values of the pattern-weight ratio equal to 2 or 3. The dynamic sample selection approach, presented in this article, can increase the convergence speed of first order optimization techniques, used for training MLP networks, even at the value of the pattern-weight ratio (E-FP) as high as 15 and possibly even more.

An optimum filter for extracting a time-varying harmonic signal from the noise-corrupted measurement is proposed. It is derived as a solution of the least mean square estimation with consideration of the pitch estimation error even without any assumption on the filter model. We obtain a comb-like impulse response which consists of homologous and dilated distribution of weights just located periodically with a pitch interval. This remarkable structure is well suited to the proportionally expanding error of pitch repetition times. Examples of the filter design are presented, and the performance of noise suppression is examined by comparison with conventional comb filters.

Different-wavelength distributed feedback laser diodes with integrated modulators (DFB/MODs) are fabricated on a single wafer operate at wavelengths from 1. 52 µm to 1. 59 µm, a range comparable to the expanded Er-doped fiber amplifier gain band. A newly developed field-size-variation electron-beam lithography enables grating pitch to be controlled to within 0. 0012 nm, and narrow-stripe selective metal-organic vapor-phase epitaxy is used to control the bandgap wavelength of laser active layers and modulator absorption layers for each channel. The channel spacing of fabricated 40-channel DFB/MODs is 214 GHz in average with a standard deviation of 0. 39 nm. Very uniform lasing and modulating performances are achieved, such as threshold currents about 10 mA and extinction ratios about 20 dB at -2 V in average. These devices have been used to demonstrate 2. 5-Gb/s transmission over 600 km of a normal fiber with a power penalty of less than 1 dB.

We have developed a multiple quantum well (MQW) electroabsorption (EA) modulator for wavelength-division multiplexing (WDM) switching systems. The fabricated MQW EA gate has low polarization and wavelength-dependent loss and high extinction ratio within the wavelength range of 1545 to 1560 nm. And by using this gate ultra-high-speed switching is achieved for WDM signals. Moreover, we optimize the EA gate for the full gain-band of an erbium-doped fiber amplifier (EDFA)(1535 to 1560 nm). This EA gate provides low polarization-dependent loss, higher extinction ratio, and high saturation input power in the wider wavelength range. These MQW EA gates will play an important role in future WDM switching systems.

In this paper, we give a solution to the problem of conflict-free access of various slices of data in parallel processor for image processing. Image processing operations require a memory system that permits parallel and conflict-free access of rows, columns, forward diagonals, backward diagonals, and blocks of two-dimensional image array for an arbitrary location. Linear skewing schemes are useful methods for those requirements, but these schemes require complex Euclidean division by prime number. On the contrary, nonlinear skewing schemes such as XOR-schemes have more advantages than the linear ones in address generation, but these schemes allow conflict-free access of some array slices in restricted region. In this paper, we propose a new XOR-scheme which allows conflict-free access of arbitrarily located various slices of data for image processing, with a two-fold the number of memory modules than that of processing elements. Further, we propose an efficient data alignment network which consists of log N + 2-stage multistage interconnection network utilizing Omega network.

It becomes essential in practice to improve a processing rate and to divide an image into small segments adjusting a limited memory, because image filing systems handle large images up to A1 size. This paper proposes a new method of an automatic skew normalization, comprising a high-speed skew detection and a distortion-free dividing rotation. We have evaluated the proposed method from the viewpoints of the processing rate and the accuracy for typed documents. As results, the processing rate is 2. 9 times faster than that of a conventional method. A practical processing rate for A1 size documents can be achieved under the condition that the accuracy of a normalized angle is controlled within 0. 3 degrees. Especially, the rotation with dividing can have no error angle, even when the A1 size documents is divided into 200 segments, whereas the conventional method cause the error angle of 1. 68 degrees.

In the future broadband networks, multicast services such as video conferencing and distance learning will become increasingly important. To support these multimedia services, one solution is to form an AMT(ATM Multicast Tree)to connect all the conferencing members. In this paper, based on AMT survivability requirements, we investigate the self-healing of an AMT. Self-healing on AMT is a new challenge of survivability of multimedia services. The pre-assign way is a method we usually considered on protection. If we construct a disjoint backup tree, the low building probability and complicated loading on constructing is the first problem. Second, if only one link or node failed on an AMT, we need to reroute links and reserve bandwidth on whole backup tree. Moreover, since the AMT usually transmits video images, the restoration rate will be decreased because even only one branch of backup tree does not endure the required bandwidth. These enhance us to restore the AMT by dynamic restoration scheme. Two proposed dynamic restoration schemes are developed to provide prioritized restoration from a link or node failure. In the first scheme, we apply a link-based restoration scheme on the AMT. The restoration is based on the failed links of network and does not take whole AMT into account. In the second scheme, without changing the multicast services to the members, we allow reconfiguration of the AMT during the restoration phase. Reconfiguration of the AMT is based on a tree-based restoration concept. By computer simulations, we verify the characteristics of the proposed schemes and the results show that the second scheme outperforms the first.

To improve speech coding quality, in particular, the long-term dependency prediction characteristics, we propose a new nonlinear predictor, i. e. , a fully connected recurrent neural network (FCRNN) where the hidden units have feedbacks not only from themselves but also from the output unit. The comparison of the capabilities of the FCRNN with conventional predictors shows that the former has less prediction error than the latter. We apply this FCRNN instead of the previously proposed recurrent neural networks in the code-excited predictive speech coding system (i. e. , CELP) and shows that our system (FCRNN) requires less bit rate/frame and improves the performance for speech coding.

A VLSI implementation of a low-power DSP core is described, which is dedicated to the G. 723. 1 low bitrate speech codec. A number of sophisticated DSP microarchitectures are devised mainly on dual multiply accumulators, rounding and saturation mechanisms, and two-banked on-chip memory. The main attempt is focused on lowering the clock frequency, and therefore on reducing the total power consumption, at the cost of a fairly small increase of chip area. The proposed DSP architecture has been integrated in the total area of 7. 75 mm2 by using a 0. 35 µm CMOS technology, which can operate at 10 MHz with the dissipation of 44. 9 mW from a single 3 V supply.

In this paper, we propose flow aggregation algorithms for multicast video transport. Because of heterogeneities of network/client environments and users' preference on the perceived video quality, various QoS requirements must be simultaneously guaranteed even for the single video source in the multicast connection. It is easy but ineffective to provide many video streams according to each user's request. Our flow aggregation algorithm arranges similar QoS requirements of clients into a single QoS requirement, by which the required number of video streams that the video server prepares can be decreased. Then the total amount of the required bandwidth can be reduced by sharing the same video stream among a number of clients. Our flow aggregation algorithm has two variants, which are suitable to sender-initiated and receiver-initiated multicast connections, respectively. Proposed algorithms are evaluated and compared through simulation. Then we show that the server-initiated flow aggregation (an ideal case in our approach) is most effective, but the receiver-initiated flow aggregation can also offer a reasonably effective mechanism.

This paper studies the routing algorithms for multi-destination connections where each destination may require different amount of data streams. This asymmetric feature can arise mostly in a large and/or heterogeneous network environment. There are mainly two reasons for this. One is that terminal equipments may have different capabilities. The other is that users may have various interests in the same set of information. We first define the asymmetric multicast problem and describe an original routing method for this type of multicast. The method is then employed in the presented routing algorithms, which can be run in multi-cluster environment. The multi-cluster architecture is considered to be effective for running routing in the networks, where a variety of operating methods might be applied in different clusters but global network performance is required. Our algorithms are designed based on some classical Steiner tree heuristics. The basic goal of our algorithms is to make routing decisions for the asymmetric multicast connections with minimum-cost purpose. In addition, we also consider delay constraint requirements in the multicast connections and propose correspondent algorithms. We compare the performance between SPT (Shortest Path Tree)-based algorithms and the presented algorithms by simulations. We show that performance difference exists among the different types of the algorithms.